Multi-agent Exploration Simulator for 3D Space (MAES3D) is an open-source framework developed in Unity for testing and comparing exploration and coverage algorithms (Biegel et. al). This paper proposes to further expand upon the framework by addressing shortcomings and implementing new features missing from the prior iteration of the framework. These changes include an improvement of the sensing capabilities of agents allowing them a longer sensing range, a visualization of the explored areas, a more configurable map generator, and an improved camera and user interface. Furthermore, a novel exploration algorithm called Dual-Stage Viewpoint Planner (DSVP) is translated from 2D using a single robot to 3D with multiple robots. Experiments are conducted to compare the performance of DSVP and the already implemented algorithms named Random Ballistic Walk (RBW) and Local Voronoi Decomposition (LVD). The results of the experiments show that RBW is outperformed by both LVD and DSVP, with DSVP as the concise winner. Finally, a performance test shows that MAES3D is able to simulate at least 10 agents simultaneously.